Path: /authentication/password

from chainlit.types import AppUser
ImportError: cannot import name 'AppUser' from 'chainlit.types' (/opt/conda/envs/wiki/lib/python3.8/site-packages/chainlit/types.py)

Hi Team,

Thanks a lot for the wonderful work. I know more documentation will be available in future, but here is some questions I have if you can help me.

Are there any ways to use multiple worker while deploying in production?
Are there any default setting of number of worker when we run 'chainlit run myapp.py'
Where does the session stored? (In case I want to run with multiple workers, can I assume that for a particular session it can always find its session variable ? in cloud the assigned worker for a request can be changed for a single session unless session affinity is in place)

[UI]
# Name of the app and chatbot.
name = "ensu"
custom_css = '/public/stylesheet.css'

it is not working

I am trying to run open-interpreter from the cookbook and keep getting this error:

module_path = registry[name]
                  ~~~~~~~~^^^^^^
KeyError: 'on_file_upload' 

Do I need to make any change?
Thanks

There is only code for config file but there is no code for voice input for chainlit so please provide the code for voice input in chainlit

Path: /examples/openai-sql

It is using version 1.0.0; however, chainlit version has been updated to 1.0.502 which does not support to_openai(). Kindly, suggest an alternative to this function for streaming responses.

Path: /examples/qa

Chainlit version 0.6.2
https://docs.chainlit.io/examples/qa

Error on UI screen: Message.init() got an unexpected keyword argument 'disable_human_feedback'

\site-packages\chainlit\utils.py", line 36, in wrapper
return await user_function(**params_values)

I couldn't make the text (and image) elements to display as is described in the docs on /api-reference/elements/text

The only way that seems to work is with message context and display = "inline". All the other described versions (outside of message context, and other display types, didn't show the elements at all. What am I doing wrong? Or is the doc outdated?

Being able to display text or image permanently, out of a message context, would be extremely helpful.

Thanks.

Path: /data-persistence/feedback

Exception: [{'message': 'Unknown type "FeedbackPayloadInput". Did you mean "ThreadPayloadInput", "GenerationPayloadInput", or "ScorePayloadInput"?', 'locations': [{'line': 14, 'column': 22}]}, {'message': 'Unknown argument "feedback" on field "Mutation.ingestStep".', 'locations': [{'line': 31, 'column': 9}]}]
2024-04-29 12:46:12 - HTTP Request: POST https://cloud.getliteral.ai/api/graphql "HTTP/1.1 200 OK"
2024-04-29 12:46:12 - Failed to create feedback: [{'message': 'Unknown type "FeedbackStrategy".', 'locations': [{'line': 5, 'column': 24}]}, {'message': 'Cannot query field
"createFeedback" on type "Mutation".', 'locations': [{'line': 8, 'column': 13}]}]

I get the following error when clicking on the "Inspect in prompt playground" icon.
"Prompt Playground error: No LLM provider available"

If I set the .env file(include the OPENAI_API_KEY and OPENAI_API_BASE), there is no this problem.

but I what to set it with the config ? how the set the env? Is there some example?

When I try to run local Data Persistence, it gave me the following error

2023-08-19 02:31:01 - Your app is available at http://localhost:8000
2023-08-19 02:31:02 - HTTP Request: GET http://localhost:63750/status "HTTP/1.1 502 Bad Gateway"
ERROR: Traceback (most recent call last)
Why is the port for Prisma so off?

When I type something on the localhost board and send it, three messages are returned:

LLMChain: not a valid model id
Chatbot: not a valid model id
Error: not a valid model id

I have changed the environment variable : export GPT_MODEL="gpt-3.5-turbo"
Is it correct? Please help me.

Path: /integrations/llama-index

The llama_index has changed. i've been able to make up for it with llama_index.core, but the import of LLMPredictor causes an import error .

Can you help ?

Thanks a lot

Path: /api-reference/lifecycle-hooks/on-message
@cl.on_chat_start works fine but , @cl.on_message is not working although I have followed the documentation.

Path: /examples/openai-sql

Path: /integrations/langchain

I installed langchain + chainlit, set my .env with my openAI key, and copied the async LCEL code identically to my app.py.

When I run "chainlit run app.py -w" it shows:

In terminal, it shows: You need to configure at least an on_chat_start or an on_message callback but it's clearly defined in the default code.

Any sense what I could have done wrong here?

Hi Team,

are there any sample code for chainlit and react together to handle document attachment from custom react frontend screen and chainlit as backend. The example works fine when chainlit as frontend, but if I want to have custom react frontend and chainlit as backend, are there any sample code for react code?. Thanks in advance

I’m sorry, I made this issue by mistake…

Path: /concepts/feedback

https://docs.chainlit.io/cloud/persistence/custom link on documentation page for custom data persistence is broken,

Hi All,

I am sqlite as data persistence layer and Microsoft Authentication. I want to fix chat resume feature for my application. Can anyone help me with that.

Here is my code.

@cl.on_chat_resume
async def on_chat_resume(thread: cl_data.ThreadDict):
memory = []
root_messages = [m for m in thread["steps"] if m["parentId"] == 'None']
for message in root_messages:
if message["type"] == "user_message":
memory.append({"role": "user", "content": message["output"]})
else:
memory.append({"role": "assistant", "content": message["output"]})
cl.user_session.set("memory", memory)
await cl.Message(memory).send()![Uploading Screenshot from 2024-04-02 17-51-59.png…]()

Path: /observability-iteration/chain-of-thought

Path: /authentication/password
cl.AppUser should be transitioned to the new cl.User

Path: /integrations/langflow

I don't think this example works.. i get this error:

2023-09-13 11:41:13 - load_flow_from_json() got an unexpected keyword argument 'flow'
Traceback (most recent call last):
File "/Users/simonau/Documents/Lending/env/lib/python3.11/site-packages/chainlit/utils.py", line 40, in wrapper
return await user_function(**params_values)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/simonau/Documents/Lending/main_tool_langflow.py", line 15, in start
flow = await load_flow(schema=schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Users/simonau/Documents/Lending/env/lib/python3.11/site-packages/chainlit/langflow/init.py", line 30, in load_flow
flow = load_flow_from_json(flow=schema, tweaks=tweaks)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
TypeError: load_flow_from_json() got an unexpected keyword argument 'flow'
2023-09-13 11:41:13 - load_flow_from_json() got an unexpected keyword argument 'flow'

Path: /api-reference/elements/text

Path: /chat-experience/loader

Hello,

I don't know if it's voluntary,
But it should be added that if, in config.toml, we have hide_cot like this:

# Hide the chain of thought details from the user in the UI.
hide_cot = true

Then the loader won't be displayed.

I was following the tutorial to display the loader (running) while awaiting for the response, but it is not working.
I just copy the code from the documentation.

import chainlit as cl

@cl.on_chat_start
async def main():
    msg = cl.Message(content="Hello!")
    await msg.send()

    await cl.sleep(2)

    msg.content = "Hello again!"
    await msg.update()

It appears Hello, after a few seconds appears Hello Again, but the loader is not shown

Path: /api-reference/elements/avatar

about the avatar, is there a way to hide it?

I'm trying to collect the data from human feedback (negative feedback & positive feedback & additional feedback).

But I couldn't find any callback function that the "Submit feedback" button invoke.

Is there any Python decorator that can catch the event or any way to solve the problem?

Path: /overview when save the response in a variable (user_reply1), im getting an ID, but i need the response provided by the user
user_reply1 = await cl.Message(content="Huh Sure, i can help you on that,can I proceed? (yes/no) ").send()
print("user_reply1", user_reply1) # for this i got "ee77a057-5b53-437b-9ecd-54d5a99b01a8", but i need the user response
if user_reply1 == "yes":
await cl.Message(content="event will be created").send()
if user_reply1 == "no":
await cl.Message(content="what do you like to know").send()
can anyone help me ?

Path: /advanced-features/test-debug

The following code snippet is shared on this documentation page re Testing & Debugging:

if __name__ == "__main__":
    from chainlit.cli import run_chainlit
    run_chainlit(__file__)

This snippet appears to simply launch a Chainlit application.

For headless testing in automation we need to be able and execute tests without a Chainlit application, but with context, etc.

Path: /api-reference/chat-settings

I am unable to run chainlit on my system.
When I run chainlit run app.py -w it says - 2023-09-27 19:29:08 - Your app is available at http://localhost:8000
That time http://localhost:8000/ says - Not Found
The requested URL was not found on the server. If you entered the URL manually please check your spelling and try again.

Path: /api-reference/message

This stream is not maintaining format of original content passed by token_list. It should stream in same format as original response.

Path: /api-reference/on-message

Path: /api-reference/integrations/langchain
This is my code:
from langchain_community.document_loaders import PyPDFLoader, DirectoryLoader
from langchain.prompts import PromptTemplate
from langchain_community.embeddings import HuggingFaceEmbeddings
from langchain_community.vectorstores import FAISS
from langchain_community.llms import CTransformers
from langchain.chains import RetrievalQA

from langchain_community.chat_loaders.whatsapp import WhatsAppChatLoader

from langchain_openai import AzureChatOpenAI

from langchain_community.chat_loaders.base import ChatSession

from langchain_community.chat_loaders.utils import (

map_ai_messages,

merge_chat_runs,

)

import chainlit as cl
from db import handle_db_queries

DB_FAISS_PATH = 'C://Users//PRINCE CHOUDHARY//Downloads//Llama2-Medical-Chatbot-main//vectorstore//db_faiss'

custom_prompt_template = """Use the following pieces of information to answer the user's question.
If you don't know the answer, just say that you don't know, don't try to make up an answer.

Context: {context}
Question: {question}

Only return the helpful answer below and nothing else.
Helpful answer:
"""

def set_custom_prompt():
"""
Prompt template for QA retrieval for each vectorstore
"""
prompt = PromptTemplate(template=custom_prompt_template,
input_variables=['context', 'question'])
return prompt

#Retrieval QA Chain
def retrieval_qa_chain(llm, prompt, db):
qa_chain = RetrievalQA.from_chain_type(llm=llm,
chain_type='stuff',
retriever=db.as_retriever(search_kwargs={'k': 2}),
return_source_documents=True,
chain_type_kwargs={'prompt': prompt}
)
return qa_chain

#Loading the model
def load_llm():
# Load the locally downloaded model here
llm = CTransformers(
#model = "TheBloke/Llama-2-7B-Chat-GGML",
model="C://Users//PRINCE CHOUDHARY//Downloads//Llama2-Medical-Chatbot-main//llama-2-7b-chat.ggmlv3.q8_0.bin",
model_type="llama",
max_new_tokens = 512,
temperature = 0.5
)
return llm

#QA Model Function
def qa_bot():
embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-L6-v2",
model_kwargs={'device': 'cpu'})
db = FAISS.load_local(DB_FAISS_PATH, embeddings, allow_dangerous_deserialization=True)
llm = load_llm()
qa_prompt = set_custom_prompt()
qa = retrieval_qa_chain(llm, qa_prompt, db)

return qa

#output function
def final_result(query):
qa_result = qa_bot()
response = qa_result({'query': query})
return response

#chainlit code
@cl.on_chat_start
async def start():
chain = qa_bot()
if chain is None:
print("Failed to initialize chain object")
else:
msg = cl.Message(content="Starting the bot...")
await msg.send()
msg.content = "Hi, Welcome to BotVerse. What is your query?"
await msg.update()

    cl.user_session.set("chain", chain)

@cl.on_message
async def main(message: cl.Message):
chain = cl.user_session.get("chain")
cb = cl.AsyncLangchainCallbackHandler(
stream_final_answer=True, answer_prefix_tokens=["FINAL", "ANSWER"]
)
cb.answer_reached = True
if chain is None:
print("Error: The chain is not initialized.")
else:
# Determine if the message is a database query
if "Chinook DB" in message.content: # This is a simple example condition
response = handle_db_queries(message.content)
else:
# Use the existing chain for other types of queries
response = await chain.acall(message.content, callbacks=[cb])

    answer = response.get("result") if isinstance(response, dict) else response
    sources = response.get("source_documents") if isinstance(response, dict) else None

    if sources:
        answer += f"\nSources:" + str(sources)
    else:
        answer += "\nNo sources found"
    await cl.Message(content=answer).send()

On running the application This issue is coming up:
C:\Users\PRINCE CHOUDHARY\Downloads\Llama2-Medical-Chatbot-main\venv\lib\site-packages\langchain_core_api\deprecation.py:117: LangChainDeprecationWarning: The function acall was deprecated in LangChain 0.1.0 and will be removed in 0.2.0. Use ainvoke instead.
warn_deprecated(

Can anyone help with thr issue?

Add Cognito to Oauth examples here https://docs.chainlit.io/authentication/oauth

Path: /integrations/langchain

This is a suggestion for a minor improvement of the LangChain integration docs.

Environment

• Python v3.11.6
• chainlit v0.7.603
• MacOS Sonoma v14.0
• VS Code Pylance extension v2023.11.10, powered by the static type checker Pyright

Problem

The below code, generates an inconvenient warning from Pylance in VS Code.

Code:

runnable = cl.user_session.get("runnable")  # type: Runnable

Warning:

Expression of type "Unknown | None" cannot be assigned to declared type "Runnable[Unknown, Unknown]"
Type "Unknown | None" cannot be assigned to type "Runnable[Unknown, Unknown]"
Type "None" cannot be assigned to type "Runnable[Unknown, Unknown]" Pylance(reportGeneralTypeIssues)

Pylance suggests that the code cannot guarantee that the .get("runnable") call returns a Runnable.

This is an inconvenience when copy-pasting to get started with chainlit.

Solution

I suggest you change the docs to the following, to inform the type checker that we will always receive a value with the type Runnable:

from typing import cast

# (..)

runnable = cast(Runnable, cl.user_session.get("runnable"))

# (...)

Would make a PR directly, but the repo seems to require me to create a fork, so I'm taking the lazy route and just raising an issue ;-)

Potential Limitations

1. typing.cast was introduced in Python 3.5 together with the typing module, so if you only support Python v3.5+, this change should work for everyone. If it's correct that chainlit currently supports >=3.8.1 and <3.12, the change should be fine.

2. Have not tested this with any other type checker.

Path: /examples/openai-sql

When I ran the app I got this AttributeError: 'dict' object has no attribute 'to_openai'?

The script snippet at https://docs.chainlit.io/deployment/copilot needs to be updated to include this listener, which appears to the correct way to do this in the cookbook and the community.

    window.addEventListener("chainlit-call-fn", (e) => {
      const { name, args, callback } = e.detail;
      if (name === "test") {
        callback("You sent: " + args.msg);
      }
    });

Should solve Chainlit/chainlit#929

Path: /advanced-features/prompt-playground/setup

The code on this page does not work until an LLM provider is configured, which is only mentioned 2 pages later here. I suggest either mentioning the dependency or changing the order of pages.

how to use the Public Apps & Environment Variables

• langchain == 0.2.0
• openai == 1.30.1

Path: /backend/env-variables
https://docs.chainlit.io/backend/env-variables

Public Apps & Environment Variables
If you want to share your app to a broader audience, you should not put your own OpenAI API keys in the .env file. Instead, you >should use user_env in the Chainlit config to ask each user to provide their own keys.
You can then access the user’s keys in your code using:

user_env = cl.user_session.get("env")

Code and Python and Pkgs

I don't fully understand the above settings.
Here is my sample code:

"""Python file to serve as the frontend"""
import os
import sys
sys.path.append(os.path.abspath('.'))

from openai import AsyncOpenAI
import chainlit as cl
 
from dotenv import load_dotenv
load_dotenv()

# user_env = cl.user_session.get("OPENAI_API_KEY")
# os.environ["OPENAI_API_KEY"] = user_env["OPENAI_API_KEY"]

api_key = os.environ.get("OPENAI_API_KEY")
client = AsyncOpenAI(api_key=api_key)

# Instrument the OpenAI client
cl.instrument_openai()

settings = {
    "model": "gpt-3.5-turbo",
    "temperature": 0,
    # ... more settings
}


# @cl.on_chat_start
# async def on_start():
#     await cl.Message("Hello world from Caihao Cui!").send()

@cl.on_settings_update
async def on_settings_update(settings: dict):
    print("Settings updated:", settings)


@cl.on_message
async def on_message(message: cl.Message):

    user_env = cl.user_session.get("user_env")
    api_key = user_env["OPENAI_API_KEY"]
    open.api_key = api_key
    
    # Instrument the OpenAI client
    cl.instrument_openai()
    response = await client.chat.completions.create(
        messages=[
            {
                "content": "You are a helpful bot, you always reply in English",
                "role": "system"
            },
            {
                "content": message.content,
                "role": "user"
            }
        ],
        **settings
    )
    await cl.Message(content=response.choices[0].message.content).send()


if __name__ == "__main__":
    from chainlit.cli import run_chainlit
    run_chainlit(__file__)

moreover in the '.chainlit/config.toml' I made this change.

...
# List of environment variables to be provided by each user to use the app.
user_env = ["OPENAI_API_KEY"]
...

Environment Setting (Python 3.11.9):

chainlit == 1.1.101
langchain == 0.2.0
openai == 1.30.1
streamlit == 1.34.0
streamlit-chat == 0.1.1

Issue / Error message

2024-05-19 16:09:34 - Loaded .env file
2024-05-19 16:09:35 - Your app is available at http://localhost:8000
2024-05-19 16:09:36 - Translation file for en not found. Using default translation en-US.
2024-05-19 16:09:37 - Translated markdown file for en not found. Defaulting to chainlit.md.
2024-05-19 16:09:40 - 'NoneType' object is not subscriptable
Traceback (most recent call last):
  File "/Users/PROJECTG_ROOT/.venv/lib/python3.11/site-packages/chainlit/utils.py", line 40, in wrapper
    return await user_function(**params_values)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/UsersPROJECTG_ROOT/demo_app/main.py", line 41, in on_message
    api_key = user_env["OPENAI_API_KEY"]
              ~~~~~~~~^^^^^^^^^^^^^^^^^^
TypeError: 'NoneType' object is not subscriptable
2024-05-19 16:09:48 - Translation file for en not found. Using default translation en-US.
^C% 

'dict' object has no attribute 'to_openai'

Path: /examples/mrkl

The link at the top of the page to LangChain MRKL is not working.
Example inspired from the [LangChain doc](https://python.langchain.com/en/latest/modules/agents/agents/examples/mrkl_chat.html)

Maybe they moved to this page?
https://python.langchain.com/docs/modules/agents/how_to/custom_mrkl_agent

I can fix it for you if you would like.

Path: /api-reference/input-widgets/select

Error reloading module: No module named 'chainlit.input_widget'

When using the example code.

Path: /api-reference/integrations/langchain

These are outdated now: https://docs.chainlit.io/api-reference/integrations/langchain#asynchronous-callback-handler

Attempting to run the cookbook:
https://github.com/Chainlit/cookbook/blob/main/chroma-qa-chat/app.py

chainlit run app.py -w --port 3001
2023-10-02 07:37:11 - Your app is available at http://localhost:3001
2023-10-02 07:37:21 - Anonymized telemetry enabled. See https://docs.trychroma.com/telemetry for more information.
2023-10-02 07:37:28 - module 'chainlit' has no attribute 'AsyncLangchainCallbackHandler'
Traceback (most recent call last):
  File "/home/stgeorge/anaconda3/envs/demo/lib/python3.10/site-packages/chainlit/__init__.py", line 61, in wrapper
    return await user_function(**params_values)
  File "/data/cookbook/chroma-qa-chat/app.py", line 94, in main
    cb = cl.AsyncLangchainCallbackHandler(
AttributeError: module 'chainlit' has no attribute 'AsyncLangchainCallbackHandler'

Please remove these docs as they are outdated and create confusion as to what is actually in the API.

ok

Path: /backend/config/project

This is the first of 3 sections under Config, and I'd expect to see it in the sidebar under Backend/Config right after Overview, but it doesn't show up in the sidebar. It also doesn't contain navigation links to previous/next.

Path: /get-started/deployment

Instead of linking to a guide or template for setting up a Chainlit deployment with render.com, link goes to the Discord invite.

Path: /get-started/pure-python

Error with the command below:

$ chainlit run app.py -w
2023-12-17 22:41:45 - Your app is available at http://localhost:8000
message async handler error
Traceback (most recent call last):
File "C:\Python311\Lib\site-packages\socketio\async_server.py", line 545, in _handle_connect
success = await self._trigger_event(
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Python311\Lib\site-packages\socketio\async_server.py", line 631, in _trigger_event
ret = await handler(*args)
^^^^^^^^^^^^^^
TypeError: connect() missing 1 required positional argument: 'auth'

Path: /examples/openai-sql

I tried running this example and it seems that the Prompt Playground doesn't work.

I get the following error when clicking on the "Inspect in prompt playground" icon.

"Prompt Playground error: No LLM provider available"